A. Field of the Invention
The present invention relates generally to plaque removal and whitening capabilities for toothbrushes and toothpastes, and, more particularly to a computer-implemented system and method for automatically evaluating the efficacy of plaque removal and whitening capabilities for different toothbrushes and toothpastes.
B. Description of the Related Art
Gum (or periodontal) disease, including dental plaque, is problematic in American and European households. Almost seventy-five percent of Americans and Europeans suffer from gum disease and plaque to some extent. While removal of plaque using dental cleaning devices is an effective method for plaque control, such removal techniques require frequent visits to the dentists which are time-consuming and expensive. Brushing one's teeth is one of the most economical and time-effective method of plaque control. However, negligible work has been done on the analysis of the efficaciousness of tooth brushing methods to maintain gingival health. While the toothbrush features that control plaque removal, such as, e.g., handle size, head size, bristle configurations, bristle patterns, etc. are well-known, no work has been done to date on the efficacy of brush design for plaque removal on a tooth-by-tooth basis.
Recently, a system to determine plaque removal efficacy was implemented. The system measured the plaque on teeth as disclosed by the fluorescence of the teeth under ultraviolet (“UV”) light. UV light makes plaque on teeth fluoresce as a yellow color, enamel as a light blue color, gum as a black color, and plaque on gum as a green color. In the system a set of each patient's front teeth was visually and manually overlaid with a synthetic template set for alignment, and then a digital image of the manually-aligned teeth was obtained. A simple Mahalanobis-distance based classifier was used to classify each pixel as plaque or enamel. The Mahalanobis distance is a very useful algorithm for determining the similarity of a set of values from an unknown sample to a set of values measured from a collection of known samples. The ratio of plaque versus enamel yielded a measure of percentage plaque on each patient for all the teeth combined. Resultant analyses before and after brushing allowed a measure of the efficacy of plaque removal for each toothbrush.
This system suffers from several drawbacks. First, it does not measure plaque removal efficacy for each tooth, and does not consider plaque measurements from teeth inside the mouth or on the inner (i.e., lingual) tooth surface. This is a significant disadvantage since some toothbrushes could remove plaque from teeth at the front of the mouth, but not remove plaque from the teeth in the interior of the mouth due to insufficient reach. Second, the alignment procedure of the system is visually performed and inconsistent since individual teeth vary widely from the synthetic set used in the system.
Recently, a robot-based brushing system was introduced to test plaque removal on synthetic teeth (“typodonts”). Synthetic plaque was coated onto the typodonts and different brush heads were used to brush the synthetic teeth using the robot-based brushing system. A simple image processing system was used to measure the plaque remaining after brushing. The image processing task was simple because the plaque on teeth could be easily distinguished from enamel and gum using the RGB values. Though this system is consistent since the brushing action does not vary much, the use of synthetic plaque is not realistic and does not reflect the presence of plaque on real teeth accurately. Nor does the system accurately reflect brushing actions in the mouth where the hard-to-reach teeth typically get brushed less than the front teeth
Thus there is a need in the art for an automated system for analyzing plaque and whitening on a tooth-by-tooth basis in real-time to assist in the determination of the usefulness of new toothbrushes and toothpastes.